Abstract
Cloud computing has become the main source for executing scientific experiments. It is an effective technique for distributing and processing tasks on virtual machines. Scientific workflows are complex and demand efficient utilization of cloud resources. Scheduling of scientific workflows is considered as NP-complete. The problem is constrained by some parameters such as Quality of Service (QoS), dependencies between tasks and users’ deadlines, etc. There exists a strong literature on scheduling scientific workflows in cloud environments. Solutions include standard schedulers, evolutionary optimization techniques, etc. This article presents a hybrid algorithm for scheduling scientific workflows in cloud environments. In the first phase, the algorithm prepares tasks lists for PSO algorithm. Bottleneck tasks are processed on high priority to reduce execution time. In the next phase, tasks are scheduled with the PSO algorithm to reduce both execution time and monetary cost. The algorithm also monitors the load balance to efficiently utilize cloud resources. Benchmark scientific workflows are used to evaluate the proposed algorithm. The proposed algorithm is compared with standard PSO and specialized schedulers to validate the performance. The results show improvement in execution time, monetary cost without affecting the load balance as compared to other techniques.
Highlights
Cloudcomputing has shifted computing from traditional way to a fascinating and impressive era of computing
The services are influenced by non-functional Quality of Service (QoS) parameters such
Workflow tasks have dependencies represented as G = (V, E), where V refers to the vertices and represents tasks in workflow and E refers to edges and represents dependencies between tasks
Summary
Cloudcomputing has shifted computing from traditional way to a fascinating and impressive era of computing. As opposed to traditional computing, where users need to maintain in-house infrastructure, cloud computing avoids this requirement and provides services as per user demand and use. The users do not need to purchase and maintain hardware, storage and processing, etc. The data are stored and accessed via the Internet [1], [2]. Cloud users can access their data anytime from anywhere. Cloud computing environment is flexible and scalable that facilitates the users to lease or release services as per need. Users can lease services with long term reservation plans or short term dynamic plans [4]. Many cloud services providers provide similar services such as computing, storage and network services. The services are influenced by non-functional Quality of Service (QoS) parameters such
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